By Adi Reschenhofer, CEO, CyberTrap
Every few months, someone publishes a think piece about how the SIEM is dead. How it's legacy. How you need to rip it out and start over.
That's wrong. And it's expensive advice.
Your SIEM isn't the problem. What it's missing is.
Legacy SIEMs do one thing well: correlation. They take thousands of events and find patterns. Rules fire. Alerts surface. Dashboards turn amber.
What they cannot do is confirm.
Correlation tells you something looks suspicious. Confirmation tells you an adversary actually engaged with something they should never have touched. Those are not the same thing. The gap between them is where analysts burn out, where real attacks hide, and where security budgets disappear without anyone being able to prove the stack is actually working.
Correlation without confirmation is not a detection capability. It is an alert generator. And it has been the dirty secret of enterprise security operations for fifteen years.
71% of SIEM alerts are false positives. That number has barely moved in a decade. Not because teams aren't trying — because the problem is structural, not operational.
You can tune rules forever. You can raise thresholds, build more sophisticated correlation logic, layer in more enrichment sources. At the end of it you are still working with probabilistic signals. Something looked like an attacker. Something behaved like lateral movement. Something crossed a threshold that was designed to approximate a threat.
Approximate is the word that matters. Because approximation is all a SIEM can ever give you. Every signal it ingests comes from systems that were never designed to prove hostile intent. They were designed to log behaviour. Logging behaviour and proving intent are fundamentally different operations, and no amount of tuning converts one into the other.
I've watched smart SOC teams spend months on this. It helps at the margins. The structural problem remains.
When you place assets in your environment that have no legitimate use — fake credentials, honeypot services, decoy shares, digital twins — you are not adding another detection layer. You are adding a completely different kind of signal.
Any interaction with a deception asset is, by definition, confirmed hostile intent. There is no threshold to calibrate. No probability to weigh. No false positive to chase down. An entity touched something it could only have touched if it was actively probing your environment. That's not an indicator of compromise. That's proof of one.
And when that signal flows back into your SIEM, everything around it changes. The three ambiguous alerts from the same time window suddenly have an anchor. Something confirmed hostile was present in that segment. Those alerts no longer require a judgment call. They require a response.
This is the missing link. Not a new platform. Not a rip-and-replace project. A confirmation layer that sits over the infrastructure you already have and answers the one question your SIEM has never been able to answer cleanly: is this real?
Even with better signals, there is a second structural problem that tuning will never touch: a SIEM processes events in isolation.
An attacker who takes three weeks to move from initial access to lateral movement is essentially invisible to rule-based detection. Each step stays below threshold. The identity anomaly on day two looks unrelated to the credential access on day nine. The unusual process chain on day fourteen doesn't connect back to either. All of it is in the logs. None of it becomes a story.
This is where temporal reasoning matters.
A temporal knowledge graph doesn't process events — it builds a continuously evolving model of how entities, identities, and assets behave in relation to each other over time. It tracks not just what happened, but how behaviour is shifting. It sees trajectory. A SIEM sees snapshots.
When deception confirms that a hostile entity is present, temporal reasoning answers the next question: how long has it been here, what has it touched, and in what sequence? That's what turns a confirmation into a case an analyst can actually work.
Picture this. Three SIEM alerts in nine minutes — an identity anomaly, a suspicious process chain, an SMB access pattern barely crossing threshold. Independently, none of them justify waking incident response. Together, concerning but still not conclusive.
Then deception confirms it. The same identity accessed a credential lure seeded for that segment. A decoy share that no legitimate user would ever touch was reached.
Then temporal reasoning contextualises it. That same identity showed a behavioural shift twelve days ago. It accessed two systems it had never touched before. It appeared in an authentication sequence the SIEM logged and correlated to nothing.
Now the analyst is not looking at three disconnected alerts. They are looking at a twelve-day attack timeline with confirmed hostile intent, a full sequence of affected systems, and no ambiguity about what to do next.
The SIEM had every piece of this. It had been correlating for twelve days. What it never had was confirmation — and a reasoning layer to show what that confirmation meant across time.
Legacy SIEMs offer correlation without confirmation. That is the missing link. Everything else — the alert fatigue, the analyst burnout, the attacks that move undetected for weeks, the inability to show the board that the stack is actually working — traces back to it.
The answer is not to replace what you have. The answer is to give it what it has always lacked.
CyberTrap sits on top of your existing SIEM. Same data. Fundamentally different results.
Adi Reschenhofer is CEO of CyberTrap. CyberTrap Engage combines deception-based signal validation with temporal AI reasoning — built for SOC teams who need confirmation, not just correlation. cybertrap.com